The Impact of AI Adoption on Project Scheduling Efficiency in Real Estate Development Projects in Nairobi

Abstract

The adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies in real estate project management has resulted to the enhancement of project scheduling efficiency. As such, this study investigated how AI has enhanced the optimization of project schedules within the real estate sector in the Nairobi Metropolitan Area. A mixed research method approach was employed in which the research integrated qualitative data collected through interviews with project managers and quantitative data obtained from project records to evaluate the impact of AI on key scheduling metric. The metrics include Schedule Performance Index (SPI) and the Critical Path Length Index (CPLI). The findings of this study reveal that the adoption of AI can lead to tremendous improvements in scheduling efficiency hence leading to a reduction in project delays and thus leading to effective schedule adjustments. AI tools have also proven to contribute to better resource allocation and cost control which leads to smoother project execution. However, the adoption of AI still face challenges such as high implementation costs, data privacy concerns, and a shortage of skilled personnel. Therefore, this study concludes that while AI offers a greater potential in the enhancement of project scheduling, it is still worth addressing the identified challenges to be able to maximize its benefits. This study recommends that real estate companies should invest in AI training amongst its staff and also a cost-effective AI solutions for smaller firms should be developed to benefit all stake holders in the real estate field. There should also be a robust implementation of data privacy policies to improve the security of those using AI in managing their projects.